largest publicly held personal lines property and casualty insurer in the United States.
Develops and implements predictive models using statistics/machine learning techniques for solving different business problems
Identifies data driven insights and actionable recommendations to influence business decisions by effectively communicating modeling concepts and results across functional groups
Develops analytic “story” and visual presentation strategies to ensure data is conveyed in meaningful and interpretive formats for all audience levels.
Analyzes structured and unstructured data from a number of sources to identify drivers
Reviews results, identifies variances to planned performance, analyzes causes of variance and make actionable recommendations to frontline leaders
Requirements
Proficiency in open data science tool kits, like R, Python is a must
Experience analyzing third party and syndicated data for benchmarking
Experience with Microsoft Office Suite (Excel, PowerPoint)
Strong oral communication, administrative and business writing skills
Advanced time management skills including ability to handle multiple projects, prioritize and organize
Experience Telematics, Cognitive Computing, Deep Learning, NLP, Image Analytics will be strongly preferred
Experience in solving problems across function like Claims, Pricing, Customer Analytics or Life, P&C LoBs will be preferred
Proficiency in distributed computing tools like MapReduce/ MPI (Cosmos/ Hadoop/ Spark/ Hive etc) is a plus
Exposure to Big Data Ecosystem (HADOOP, PIG, HIVE, PYTHON, SPARK etc) would be a plus
Additional Information
Primary Skills
Bachelors or Masters/MBA degree in a quantitative discipline (applied mathematics, statistics, computer science, operations research or related field) and 2-4 years of related experience
Experience with leading/mentoring a team in the areas of technology as well as problem solving is a plus
Experience with descriptive statistics and exploratory data analysis
Experience with inferential and predictive statistics (hypothesis testing, confidence intervals, regression, time series, decision trees, clustering and classification, text mining)
Performs and evaluates trend analysis using basic mathematical concepts, formulas, models, techniques